Compare group means with confidence intervals

An estimation-style plot of a numeric outcome across the levels of a grouping variable: each group's mean with a confidence interval, over a backdrop of the raw (jittered) data. By showing both the estimate and its uncertainty, it conveys whether the groups differ more faithfully than a bar chart does.

Usage

group_comparison_plot(
  data,
  y,
  group,
  conf_level = 0.95,
  show_points = TRUE,
  point_alpha = 0.25,
  differences = FALSE,
  reference = NULL,
  n_boot = 5000,
  palette = NULL,
  title = NULL,
  x_lab = NULL,
  y_lab = NULL
)

Arguments

data

A data frame.

y

The numeric outcome (string or unquoted name).

group

The grouping variable (string or unquoted name).

conf_level

Confidence level for the intervals (t-based).

show_points

Whether to draw the raw data behind the means.

point_alpha

Transparency of the raw points.

differences

If TRUE, append a lower panel showing the pairwise mean difference(s) against a reference group, each with a bootstrap confidence interval, turning the plot into a full estimation plot via estimation_plot(). The return value is then a 'patchwork' object. Defaults to FALSE (the plain group-means plot, fully backward-compatible).

reference

Reference group for the difference panel when differences = TRUE; defaults to the first level of group. Ignored otherwise.

n_boot

Number of bootstrap resamples for the difference intervals when differences = TRUE. Ignored otherwise.

palette

Colours for the groups; defaults to depictr_palette().

title, x_lab, y_lab

Title and axis labels.

Value

A ggplot2::ggplot object, or a 'patchwork' object when differences = TRUE.

Details

A group with a single observation has no degrees of freedom for a t-based interval, so only its mean is drawn (no interval) and a warning is issued.

Examples

group_comparison_plot(lexical_decision, RT, condition)

group_comparison_plot(crop_yield, yield, treatment)

# Append the pairwise mean-difference panel (an estimation plot):
set.seed(1)
group_comparison_plot(crop_yield, yield, treatment, differences = TRUE)